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STA 311 Statistical Inference

The STA 311 Statistical Inference course comprises frequency theory and Bayesian methods, which is used to generate point estimates, hypothesis tests, and confidence intervals.

The statistical inference depends on the likelihood. Bayesian statistics uses probabilities associated with the evidence. Bayesian statistics examines the decision-making process to find out its likelihood for analyzing statistical inferences. This course explains the statistical techniques of Bayesian decision theory. Statistical Hypothesis Testing collects statistical data to evaluate hypotheses. Statistical methods of Bayesian decision theory use statistical tests and a priori information to evaluate hypotheses. The probability that the Bayesian method will generate a hypothesis at the end of the test. This course describes the Bayesian probability function in representing decision problems and discusses how to use the relationship between Bayesian probability and decision making to clarify those probabilities. He views them as rational levels of belief, rather than defining them in terms of preference. The characteristics of Bayesian probability are discussed and strategies for solving objections are proposed. Bayesianism considers convention as a rule of probabilistic reasoning and maximizes expected utility as a rule of decision making. He compares Bayesian statistics with classical statistics and defends Bayesian statistics against accusations of excessive subjectivity.

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List of relevant courses, in which professionals of ExpertsMinds provides online assistance:

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